In this manuscript, a controller design methodology is proposed for a CLLLC-type bidirectional resonant converter. The soft switching of all devices in this topology and the very high operating frequency lead to increased overall system efficiency. However, the dynamic nature of this converter is highly dependent on loading conditions, which proves challenging when designing the voltage and current closed loop controllers. System instability is mainly due to the high-Q resonant peaking, which is observed in the open-loop bode-plots. In this work, a controller design methodology is proposed, which accounts for the dynamics behavior due to load variations. The controller stability will be evaluated against the entire range of operating switching frequency. Both battery charging and regeneration modes will be described and analyzed. The focal contribution off this work will focus on defining the worst operating scenarios for the converter using system level modeling and analysis. In addition, the controller will be defined based on these operating points. To validate and verify the controller design methodology proposed, a 3.5 kW converter is designed with the appropriate output voltage and current loop controllers. The step response verified a stable system designed and thus proving the proposed controller design methodology.

Purpose: The purpose of this study is to describe the efforts undertaken to convert the large university campus of Jordan University of Science and Technology (JUST) into a green, resource-efficient and low-carbon campus by following an action-oriented strategy. Sustainability features of the campus were discussed and benchmarked. Challenges were identified and remedial actions were proposed. Design/methodology/approach: Taking 2015 as the baseline year, data on energy, water consumption and solid waste generation for the university campus were collected. Energy consumption for cooling, heating and transportation, besides electric power consumption, were reported, and the associated carbon dioxide (CO₂) emissions were estimated. By calculating the full time equivalent of students and employees, carbon emission and water consumption per capita were calculated. A comparison with other universities worldwide was conducted. Findings: Although located in a semiarid region with scarce water resources, JUST has set an example by greening its campus through an action-oriented approach. It was found that the per capita carbon emission for JUST campus was 1.33 ton of CO₂ equivalent, which is less than the emissions from campuses of other universities worldwide. As for water, this study revealed that the daily per capita water consumption was about 56 L, which is approximately one-third of that for students in institutions in the USA. Furthermore, the findings of this study indicated that the average solid waste generation rate was 0.37 kg per student per day compared to 0.31 kg per capita per day when considering the university community (students and employees) collectively. These figures were less and thus compare favorably to the corresponding data for other universities in both developing and developed countries. Originality/value: This research addresses the issue of greening JUST campus, which is one of the largest university campuses in the world. JUST campus is located in a semiarid, water-scarce country, which on its own poses a serious challenge. The originality and value of this study mainly stem from the facts that on the one hand, this is one of the unique and pioneering comprehensive studies of its type and, on the other hand, other universities with similar conditions can benefit from the findings of this research to meet the sustainability objectives on their campus operations.

This paper proposes a new maximum power point tracking (MPPT) algorithm for thermoelectric generators (TEG). The new-presented method is based on implementing an indirect open circuit voltage detection and short circuit current estimation methods, which will be used to directly control the TEG interface power converter, resulting in reaching the maximum power point (MPP) in minimal number of steps. Two modes of operation are used in the proposed algorithm, namely the perturb and observe (P&O) method for fine-tuning and the transient mode for coarse tracking of the MPP during fast changes that occur to the temperature gradient across the structure. A novel voltage sensing technique as well is proposed in this work, to reduce the number of voltage sensors used to control and monitor the power converter. The proposed strategy employs a novel approach to sense two different voltages using the same voltage sensor. The input and output voltage information is collected from an intermediate point in the converter. The reconstructed voltages are used in the control loops as well as for monitoring the battery output or load voltages. Simulation and experimental results are provided to validate the effectiveness of the proposed algorithm and the sensing technique.

The impact of different photovoltaic models for a combined solar array and pumped hydro storage system was investigated. Al-Wehda dam located in Harta city in the northern of Jordan was used to validate the approach. The two-diode (TD), single-diode (SD), and ideal single-diode (ISD) solar models were evaluated in terms of the solar array size, reliability, and ecological effects. The impoundment of Al-Wehda dam was taken as the upper reservoir of the pumped hydro facility of the proposed renewable energy system. It was found that the PV power is more accurately modelled by considering the recombination loss in the TD solar model. This leads to a more realistic sizing and precise system evaluation. Results were obtained using the particle swarm optimization (PSO) algorithm and the whale optimization algorithm (WOA) for validation purposes. For instance, the PSO results showed that the realistic TD model is reliable, with an index of reliability of 98.558%. Further, it is the most ecological solution with an annual emissions reduction of 21.5198 Gg. The optimized values are 44,840 solar panels and 65.052 M.m³ of the lower reservoir volume for the TD model. The number of PV panels are reduced by 16.67% and 7.93%, respectively, with the ISD and SD relative to the TD model.